Crystal structure of the lactose operon repressor and its complexes with DNA and inducer

Synthesis of C-glycoside analogues of isopropyl β-D-1-thiogalactopyranoside (IPTG) and 1-β-D-galactopyranosyl-2-methylpropane. Conformational analysis and evaluation as inhibitors of the lac repressor in E. coli and as galactosidase inhibitors

Isopropyl 1-thio-β-D-galactopyranoside (IPTG, 1) is used widely as an inducer of protein expression in E. coli and 1-β-D-galactopyranosyl-2-methylpropane (2), a C-glycoside analogue of 1, has also been identified as an inducer. Here, synthesis and study of mimetics of 1 and 2, 1-β-D-galactopyranosyl-2-methylpropan-1-ols and two cyclic acetals derivatives, that constrain the presentation of the iPr group in various geometries is described. Conformational analysis of C-glycosides in protic solvent is performed using (i) Desmond metadynamics simulations (OPLS4) and (ii) use of 3JHH values obtained by 1H-NMR spectroscopy. 1-β-D-Galactopyranosyl-2-methylpropane (2) is an effective protein expression inducer when compared to the new mimetics, which were less effective or did not induce expression. 1-β-D-Galactopyranosyl-2-methylpropane (2) led to significantly reduced proteolysis during protein expression, compared to IPTG suggesting that recombinant protein purification will be easier to achieve with 2, yielding proteins with higher quality and activity. IPTG reduced bacterial growth to a greater degree than 2 compared to the control. IPTG's isopropyl group was observed by molecular dynamics (MD) simulations to be flexible in the binding pocket, deviating from its crystal structure binding mode, without impacting other interactions. The MD simulations predicted that 1-β-D-galactopyranosyl-2-methylpropane (2) was more likely than IPTG to bind the repressor with a conformation favoured in protic solvent, while maintaining interactions observed for IPTG. MD simulations predicted that isobutanol derivatives may disrupt interactions associated with IPTG's binding mode. The compounds were also evaluated as inhibitors of galactosidases, with 2 being the more potent inhibitor of the E. coli β-galactosidase. The constrained cyclic acetals showed similar inhibition constants to IPTG indicating E. coli β-galactosidase can recognize galactopyranoses with varying presentation of the iPr group.

Transcription Attenuation in Synthetic Promoters in Nonoverlapping Tandem Formation

Closely spaced promoters are ubiquitous in prokaryotic and eukaryotic genomes. How their structure and dynamics relate remains unclear, particularly for tandem formations. To study their transcriptional interference, we engineered two pairs and one trio of synthetic promoters in nonoverlapping, tandem formation, in single-copy plasmids transformed into Escherichia coli cells. From in vivo measurements, we found that these promoters in tandem formation can have attenuated transcription rates. The attenuation strength can be widely fine-tuned by the promoters' positioning, natural regulatory mechanisms, and other factors, including the antibiotic rifampicin, which is known to hamper RNAP promoter escape. From this, and supported by in silico models, we concluded that the attenuation in these constructs emerges from premature terminations generated by collisions between RNAPs elongating from upstream promoters and RNAPs occupying downstream promoters. Moreover, we found that these collisions can cause one or both RNAPs to falloff. Finally, the broad spectrum of possible, externally regulated, attenuation strengths observed in our synthetic tandem promoters suggests that they could become useful as externally controllable regulators of future synthetic circuits.

Non-canonical start codons confer context-dependent advantages in carbohydrate utilization for commensal E. coli in the murine gut

Resource competition is a driver of gut microbiota composition. Bacteria can outcompete metabolically similar rivals through the limitation of shared growth-fuelling nutrients. The mechanisms underlying this remain unclear for bacteria with identical sets of metabolic genes. Here we analysed the lactose utilization operon in the murine commensal Escherichia coli 8178. Using in vitro and in vivo approaches, we showed that translation of the lactose utilization repressor gene lacI from its native non-canonical GTG start codon increases the basal expression of the lactose utilization cluster, enhancing adaptation to lactose consumption. Consequently, a strain carrying the wild type lacI GTG start codon outperformed the lacI ATG start codon mutant in the mouse intestine. This advantage was attenuated upon limiting host lactose intake through diet shift or altering the mutant frequency, emphasizing the context-dependent effect of a single nucleotide change on the bacterial fitness of a common member of the gut microbiota. Coupled with a genomic analysis highlighting the selection of non-ATG start codons in sugar utilization regulator genes across the Enterobacteriaceae family, our data exposed an unsuspected function of non-canonical start codons in metabolic competition.

OptoLacI: optogenetically engineered lactose operon repressor LacI responsive to light instead of IPTG

Optogenetics' advancement has made light induction attractive for controlling biological processes due to its advantages of fine-tunability, reversibility, and low toxicity. The lactose operon induction system, commonly used in Escherichia coli, relies on the binding of lactose or isopropyl β-d-1-thiogalactopyranoside (IPTG) to the lactose repressor protein LacI, playing a pivotal role in controlling the lactose operon. Here, we harnessed the light-responsive light-oxygen-voltage 2 (LOV2) domain from Avena sativa phototropin 1 as a tool for light control and engineered LacI into two light-responsive variants, OptoLacIL and OptoLacID. These variants exhibit direct responsiveness to light and darkness, respectively, eliminating the need for IPTG. Building upon OptoLacI, we constructed two light-controlled E. coli gene expression systems, OptoE.coliLight system and OptoE.coliDark system. These systems enable bifunctional gene expression regulation in E. coli through light manipulation and show superior controllability compared to IPTG-induced systems. We applied the OptoE.coliDark system to protein production and metabolic flux control. Protein production levels are comparable to those induced by IPTG. Notably, the titers of dark-induced production of 1,3-propanediol (1,3-PDO) and ergothioneine exceeded 110% and 60% of those induced by IPTG, respectively. The development of OptoLacI will contribute to the advancement of the field of optogenetic protein engineering, holding substantial potential applications across various fields.

The unreasonable effectiveness of equilibrium gene regulation through the cell cycle

Systems like the prototypical lac operon can reliably hold repression of transcription upon DNA replication across cell cycles with just 10 repressor molecules per cell and behave as if they were at equilibrium. The origin of this phenomenology is still an unresolved question. Here, we develop a general theory to analyze strong perturbations in quasi-equilibrium systems and use it to quantify the effects of DNA replication in gene regulation. We find a scaling law linking actual with predicted equilibrium transcription via a single kinetic parameter. We show that even the lac operon functions beyond the physical limits of naive regulation through compensatory mechanisms that suppress non-equilibrium effects. Synthetic systems without adjuvant activators, such as the cAMP receptor protein (CRP), lack this reliability. Our results provide a rationale for the function of CRP, beyond just being a tunable activator, as a mitigator of cell cycle perturbations.

Molecular stripping underpins derepression of a toxin-antitoxin system

Transcription factors control gene expression; among these, transcriptional repressors must liberate the promoter for derepression to occur. Toxin-antitoxin (TA) modules are bacterial elements that autoregulate their transcription by binding the promoter in a T:A ratio-dependent manner, known as conditional cooperativity. The molecular basis of how excess toxin triggers derepression has remained elusive, largely because monitoring the rearrangement of promoter-repressor complexes, which underpin derepression, is challenging. Here, we dissect the autoregulation of the Salmonella enterica tacAT3 module. Using a combination of assays targeting DNA binding and promoter activity, as well as structural characterization, we determine the essential TA and DNA elements required to control transcription, and we reconstitute a repression-to-derepression path. We demonstrate that excess toxin triggers molecular stripping of the repressor complex off the DNA through multiple allosteric changes causing DNA distortion and ultimately leading to derepression. Thus, our work provides important insight into the mechanisms underlying conditional cooperativity.

Phylogeny and structural modeling of the transcription factor CsqR (YihW) from Escherichia coli

CsqR (YihW) is a local transcription factor that controls expression of yih genes involved in degradation of sulfoquinovose in Escherichia coli. We recently showed that expression of the respective gene cassette might be regulated by lactose. Here, we explore the phylogenetic and functional traits of CsqR. Phylogenetic analysis revealed that CsqR had a conserved Met25. Western blot demonstrated that CsqR was synthesized in the bacterial cell as two protein forms, 28.5 (CsqR-l) and 26 kDa (CsqR-s), the latter corresponding to start of translation at Met25. CsqR-s was dramatically activated during growth with sulfoquinovose as a sole carbon source, and displaced CsqR-l in the stationary phase during growth on rich medium. Molecular dynamic simulations revealed two possible states of the CsqR-s structure, with the interdomain linker being represented by either a disordered loop or an ɑ-helix. This helix allowed the hinge-like motion of the N-terminal domain resulting in a switch of CsqR-s between two conformational states, "open" and "compact". We then modeled the interaction of both CsqR forms with putative effectors sulfoquinovose, sulforhamnose, sulfoquinovosyl glycerol, and lactose, and revealed that they all preferred the same pocket in CsqR-l, while in CsqR-s there were two possible options dependent on the linker structure.

Engineering and application of LacI mutants with stringent expressions

Optimal transcriptional regulatory circuits are expected to exhibit stringent control, maintaining silence in the absence of inducers while exhibiting a broad induction dynamic range upon the addition of effectors. In the Plac /LacI pair, the promoter of the lac operon in Escherichia coli is characterized by its leakiness, attributed to the moderate affinity of LacI for its operator target. In response to this limitation, the LacI regulatory protein underwent engineering to enhance its regulatory properties. The M7 mutant, carrying I79T and N246S mutations, resulted in the lac promoter displaying approximately 95% less leaky expression and a broader induction dynamic range compared to the wild-type LacI. An in-depth analysis of each mutation revealed distinct regulatory profiles. In contrast to the wild-type LacI, the M7 mutant exhibited a tighter binding to the operator sequence, as evidenced by surface plasmon resonance studies. Leveraging the capabilities of the M7 mutant, a high-value sugar biosensor was constructed. This biosensor facilitated the selection of mutant galactosidases with approximately a seven-fold improvement in specific activity for transgalactosylation. Consequently, this advancement enabled enhanced biosynthesis of galacto-oligosaccharides (GOS).

Conflicting Interfacial Electrostatic Interactions as a Design Principle to Modulate Long-Range Interdomain Communication

The extent and molecular basis of interdomain communication in multidomain proteins, central to understanding allostery and function, is an open question. One simple evolutionary strategy could involve the selection of either conflicting or favorable electrostatic interactions across the interface of two closely spaced domains to tune the magnitude of interdomain connectivity. Here, we study a bilobed domain FF34 from the eukaryotic p190A RhoGAP protein to explore one such design principle that mediates interdomain communication. We find that while the individual structural units in wild-type FF34 are marginally coupled, they exhibit distinct intrinsic stabilities and low cooperativity, manifesting as slow folding. The FF3-FF4 interface harbors a frustrated network of highly conserved electrostatic interactions-a charge troika-that promotes the population of multiple, decoupled, and non-native structural modes on a rugged native landscape. Perturbing this network via a charge-reversal mutation not only enhances stability and cooperativity but also dampens the fluctuations globally and speeds up the folding rate by at least an order of magnitude. Our work highlights how a conserved but nonoptimal network of interfacial electrostatic interactions shapes the native ensemble of a bilobed protein, a feature that could be exploited in designing molecular systems with long-range connectivity and enhanced cooperativity.

Simulated pressure changes in LacI suggest a link between hydration and functional conformational changes

The functions of many proteins are associated with interconversions among conformational substates. However, these substates can be difficult to measure experimentally, and determining contributions from hydration changes can be especially difficult. Here, we assessed the use of pressure perturbations to sample the substates accessible to the Escherichia coli lactose repressor protein (LacI) in various liganded forms. In the presence of DNA, the regulatory domain of LacI adopts an Open conformation that, in the absence of DNA, changes to a Closed conformation. Increasing the simulation pressure prevented the transition from an Open to a Closed conformation, in a similar manner to the binding of DNA and anti-inducer, ONPF. The results suggest the hydration of specific residues play a significant role in determining the population of different LacI substates and that simulating pressure perturbation could be useful for assessing the role of hydration changes that accompany functionally-relevant amino acid substitutions.

Genetic switching by the Lac repressor is based on two-state Monod-Wyman-Changeux allostery

High-resolution NMR spectroscopy enabled us to characterize allosteric transitions between various functional states of the dimeric Escherichia coli Lac repressor. In the absence of ligands, the dimer exists in a dynamic equilibrium between DNA-bound and inducer-bound conformations. Binding of either effector shifts this equilibrium toward either bound state. Analysis of the ternary complex between repressor, operator DNA, and inducer shows how adding the inducer results in allosteric changes that disrupt the interdomain contacts between the inducer binding and DNA binding domains and how this in turn leads to destabilization of the hinge helices and release of the Lac repressor from the operator. Based on our data, the allosteric mechanism of the induction process is in full agreement with the well-known Monod-Wyman-Changeux model.

Engineering allosteric transcription factors guided by the LacI topology

Allosteric transcription factors (aTFs) are used in a myriad of processes throughout biology and biotechnology. aTFs have served as the workhorses for developments in synthetic biology, fundamental research, and protein manufacturing. One of the most utilized TFs is the lactose repressor (LacI). In addition to being an exceptional tool for gene regulation, LacI has also served as an outstanding model system for understanding allosteric communication. In this perspective, we will use the LacI TF as the principal exemplar for engineering alternate functions related to allostery-i.e., alternate protein DNA interactions, alternate protein-ligand interactions, and alternate phenotypic mechanisms. In addition, we will summarize the design rules and heuristics for each design goal and demonstrate how the resulting design rules and heuristics can be extrapolated to engineer other aTFs with a similar topology-i.e., from the broader LacI/GalR family of TFs.

Can molecular dynamics be used to simulate biomolecular recognition?

There are many problems in biochemistry that are difficult to study experimentally. Simulation methods are appealing due to direct availability of atomic coordinates as a function of time. However, direct molecular simulations are challenged by the size of systems and the time scales needed to describe relevant motions. In theory, enhanced sampling algorithms can help to overcome some of the limitations of molecular simulations. Here, we discuss a problem in biochemistry that offers a significant challenge for enhanced sampling methods and that could, therefore, serve as a benchmark for comparing approaches that use machine learning to find suitable collective variables. In particular, we study the transitions LacI undergoes upon moving between being non-specifically and specifically bound to DNA. Many degrees of freedom change during this transition and that the transition does not occur reversibly in simulations if only a subset of these degrees of freedom are biased. We also explain why this problem is so important to biologists and the transformative impact that a simulation of it would have on the understanding of DNA regulation.

Clamp Interactions with +3/+6 Duplex and Upstream-to-Downstream Allosteric Effects in Late Steps of Forming a Stable RNA Polymerase-Promoter Open Complex

Stable 37 °C open complexes (OC) of E. coli RNA polymerase (RNAP) at λP_R and T7A1 promoters form at similar rates but have very different lifetimes. To understand the downstream interactions responsible for OC lifetime, how promoter sequence directs them and when they form, we report lifetimes of stable OC and unstable late (I₂) intermediates for promoters with different combinations of λP_R (L) and T7A1 (T) discriminators, core promoters and UP elements. I₂ lifetimes are similarly short, while stable OC lifetimes differ greatly, determined largely by the discriminator and modulated by core-promoter and UP elements. The free energy change ΔG₃^o for I₂ → stable OC is approximately -4 kcal more favorable for L-discriminator than for T-discriminator promoters. Downstream-truncation at +6 (DT+6) greatly destabilizes OC at L-discriminator but not T-discriminator promoters, making all ΔG₃^o values similar (approximately -4 kcal). Urea reduces OC lifetime greatly by affecting ΔG₃^o. We deduce that urea acts by disfavoring coupled folding of key elements of the β'-clamp, that I₂ is an open-clamp OC, and that clamp-closing in I₂ → stable OC involves coupled folding. Differences in ΔG₃^o between downstream-truncated and full-length promoters yield contributions to ΔG₃^o from interactions with downstream mobile elements (DME) including β-lobe and β'-jaw, more favorable for L-discriminator than for T-discriminator promoters. We deduce how competition between far-downstream DNA and σ⁷⁰ region 1.1 affects ΔG₃^o values. We discuss variant-specific ΔG₃^o contributions in terms of the allosteric network by which differences in discriminator and -10 sequence are sensed and transmitted downstream to affect DME-duplex interactions in I₂ → stable OC.

Precision engineering of biological function with large-scale measurements and machine learning

As synthetic biology expands and accelerates into real-world applications, methods for quantitatively and precisely engineering biological function become increasingly relevant. This is particularly true for applications that require programmed sensing to dynamically regulate gene expression in response to stimuli. However, few methods have been described that can engineer biological sensing with any level of quantitative precision. Here, we present two complementary methods for precision engineering of genetic sensors: in silico selection and machine-learning-enabled forward engineering. Both methods use a large-scale genotype-phenotype dataset to identify DNA sequences that encode sensors with quantitatively specified dose response. First, we show that in silico selection can be used to engineer sensors with a wide range of dose-response curves. To demonstrate in silico selection for precise, multi-objective engineering, we simultaneously tune a genetic sensor's sensitivity (EC50) and saturating output to meet quantitative specifications. In addition, we engineer sensors with inverted dose-response and specified EC50. Second, we demonstrate a machine-learning-enabled approach to predictively engineer genetic sensors with mutation combinations that are not present in the large-scale dataset. We show that the interpretable machine learning results can be combined with a biophysical model to engineer sensors with improved inverted dose-response curves.

ProX from marine Synechococcus spp. show a sole preference for glycine-betaine with differential affinity between ecotypes

Osmotic stress, caused by high or fluctuating salt concentrations, is a crucial abiotic factor affecting microbial growth in aquatic habitats. Many organisms utilize common responses to osmotic stress, generally requiring active extrusion of toxic inorganic ions and accumulation of compatible solutes to protect cellular machinery. We heterologously expressed and purified predicted osmoprotectant, proline/glycine betaine-binding proteins (ProX) from two phylogenetically distinct Synechococcus spp. MITS9220 and WH8102. Homologues of this protein are conserved only among Prochlorococcus LLIV and Synechococcus clade I, III and CRD1 strains. Our biophysical characterization show Synechococcus ProX exists as a dimer, with specificity solely for glycine betaine but not to other osmoprotectants tested. We discovered that MITS9220_ProX has a 10-fold higher affinity to glycine betaine than WH8102_ProX, which is further elevated (24-fold) in high salt conditions. The stronger affinity and effect of ionic strength on MITS9220_ProX glycine betaine binding but not on WH8102_ProX alludes to a novel regulatory mechanism, providing critical functional insights into the phylogenetic divergence of picocyanobacterial ProX proteins that may be necessary for their ecological success.

Simple mechanisms for the evolution of protein complexity

Proteins are tiny models of biological complexity: specific interactions among their many amino acids cause proteins to fold into elaborate structures, assemble with other proteins into higher-order complexes, and change their functions and structures upon binding other molecules. These complex features are classically thought to evolve via long and gradual trajectories driven by persistent natural selection. But a growing body of evidence from biochemistry, protein engineering, and molecular evolution shows that naturally occurring proteins often exist at or near the genetic edge of multimerization, allostery, and even new folds, so just one or a few mutations can trigger acquisition of these properties. These sudden transitions can occur because many of the physical properties that underlie these features are present in simpler proteins as fortuitous by-products of their architecture. Moreover, complex features of proteins can be encoded by huge arrays of sequences, so they are accessible from many different starting points via many possible paths. Because the bridges to these features are both short and numerous, random chance can join selection as a key factor in explaining the evolution of molecular complexity.

Robustness of DNA looping across multiple cell divisions in individual bacteria

DNA looping has emerged as a central paradigm of transcriptional regulation, as it is shared across many living systems. One core property of DNA looping-based regulation is its ability to greatly enhance repression or activation of genes with only a few copies of transcriptional regulators. However, this property based on a small number of proteins raises the question of the robustness of such a mechanism with respect to the large intracellular perturbations taking place during growth and division of the cell. Here we address the issue of sensitivity to variations of intracellular parameters of gene regulation by DNA looping. We use the lac system as a prototype to experimentally identify the key features of the robustness of DNA looping in growing Escherichia coli cells. Surprisingly, we observe time intervals of tight repression spanning across division events, which can sometimes exceed 10 generations. Remarkably, the distribution of such long time intervals exhibits memoryless statistics that is mostly insensitive to repressor concentration, cell division events, and the number of distinct loops accessible to the system. By contrast, gene regulation becomes highly sensitive to these perturbations when DNA looping is absent. Using stochastic simulations, we propose that the observed robustness to division emerges from the competition between fast, multiple rebinding events of repressors and slow initiation rate of the RNA polymerase. We argue that fast rebinding events are a direct consequence of DNA looping that ensures robust gene repression across a range of intracellular perturbations.

Interpretable modeling of genotype-phenotype landscapes with state-of-the-art predictive power

Large-scale measurements linking genetic background to biological function have driven a need for models that can incorporate these data for reliable predictions and insight into the underlying biophysical system. Recent modeling efforts, however, prioritize predictive accuracy at the expense of model interpretability. Here, we present LANTERN (landscape interpretable nonparametric model, https://github.com/usnistgov/lantern), a hierarchical Bayesian model that distills genotype-phenotype landscape (GPL) measurements into a low-dimensional feature space that represents the fundamental biological mechanisms of the system while also enabling straightforward, explainable predictions. Across a benchmark of large-scale datasets, LANTERN equals or outperforms all alternative approaches, including deep neural networks. LANTERN furthermore extracts useful insights of the landscape, including its inherent dimensionality, a latent space of additive mutational effects, and metrics of landscape structure. LANTERN facilitates straightforward discovery of fundamental mechanisms in GPLs, while also reliably extrapolating to unexplored regions of genotypic space.

Modulating binding affinity, specificity and configurations by multivalent interactions

Biological functions of proteins rely on their specific interactions with binding partners. Many proteins contain multiple domains, which can bind to their targets that often have more than one binding site, resulting in multivalent interactions. While it has been shown that multivalent interactions play an crucial role in modulating binding affinity and specificity, other potential effects of multivalent interactions are less explored. Here, we developed a broadly applicable transfer matrix formalism and used it to investigate the binding of two-domain ligands to targets with multiple binding sites. We show that 1) ligands with two specific binding domains can drastically boost both the binding affinity and specificity and down-shift the working concentration range, compared to single-domain ligands, 2) the presence of a positive domain-domain cooperativity or containing a non-specific binding domain can down-shift the working concentration range of ligands by increasing the binding affinity without compromising the binding specificity, 3) the configuration of the bound ligands has a strong concentration dependence, providing important insights into the physical origin of phase-separation processes taking place in living cells. In line with previous studies, our results suggest that multivalent interactions are utilized by cells for highly efficient regulation of target binding involved in a diverse range of cellular processes such as signal transduction, gene transcription, antibody-antigen recognition.

A genetic toolkit and gene switches to limit Mycoplasma growth for biosafety applications

Mycoplasmas have exceptionally streamlined genomes and are strongly adapted to their many hosts, which provide them with essential nutrients. Owing to their relative genomic simplicity, Mycoplasmas have been used to develop chassis for biotechnological applications. However, the dearth of robust and precise toolkits for genomic manipulation and tight regulation has hindered any substantial advance. Herein we describe the construction of a robust genetic toolkit for M. pneumoniae, and its successful deployment to engineer synthetic gene switches that control and limit Mycoplasma growth, for biosafety containment applications. We found these synthetic gene circuits to be stable and robust in the long-term, in the context of a minimal cell. With this work, we lay a foundation to develop viable and robust biosafety systems to exploit a synthetic Mycoplasma chassis for live attenuated vectors for therapeutic applications.

The Role of Integration Host Factor in Escherichia coli Persister Formation

Persisters represent a small subpopulation of cells that are tolerant of killing by antibiotics and are implicated in the recalcitrance of chronic infections to antibiotic therapy. One general theme has emerged regarding persisters formed by different bacterial species, namely, a state of relative dormancy characterized by diminished activity of antibiotic targets. Within this framework, a number of studies have linked persister formation to stochastic decreases in energy-generating components, leading to low ATP and target activity. In this study, we screen knockouts in the main global regulators of Escherichia coli for their effect on persisters. A knockout in integration host factor (IHF) had elevated ATP and a diminished level of persisters. This was accompanied by an overexpression of isocitrate dehydrogenase (Icd) and a downregulation of isocitrate lyase (AceA), two genes located at the bifurcation between the tricarboxylic acid (TCA) cycle and the glyoxylate bypass. Using a translational ihfA-mVenus fusion, we sort out rare bright cells, and this subpopulation is enriched in persisters. Our results suggest that noise in the expression of ihf produces rare cells with low Icd/high AceA, diverting substrates into the glyoxylate bypass, which decreases ATP, leading to antibiotic-tolerant persisters. We further examine noise in a simple model, the lac operon, and show that a knockout of the lacI repressor increases expression of the operon and decreases persister formation. Our results suggest that noise quenching by overexpression serves as a general approach to determine the nature of persister genes in a variety of bacterial species and conditions. IMPORTANCE Persisters are phenotypic variants that survive exposure to antibiotics through temporary dormancy. Mutants with increased levels of persisters have been identified in clinical isolates, and evidence suggests these cells contribute to chronic infections and antibiotic treatment failure. Understanding the underlying mechanism of persister formation and tolerance is important for developing therapeutic approaches to treat chronic infections. In this study, we examine a global regulator, IHF, that plays a role in persister formation. We find that noise in expression of IHF contributes to persister formation, likely by regulating the switch between the TCA cycle that efficiently produces energy and the glyoxylate bypass. We extend this study to a simple model lac operon and show that when grown on lactose as the sole carbon source, noise in its expression influences ATP levels and determines persister formation. This noise is quenched by overexpression of the lac operon, providing a simple approach to test the involvement of a gene in persister formation.

Sequence specificity in DNA binding is mainly governed by association

Sequence-specific binding of proteins to DNA is essential for accessing genetic information. We derive a model that predicts an anticorrelation between the macroscopic association and dissociation rates of DNA binding proteins. We tested the model for thousands of different lac operator sequences with a protein binding microarray and by observing kinetics for individual lac repressor molecules in single-molecule experiments. We found that sequence specificity is mainly governed by the efficiency with which the protein recognizes different targets. The variation in probability of recognizing different targets is at least 1.7 times as large as the variation in microscopic dissociation rates. Modulating the rate of binding instead of the rate of dissociation effectively reduces the risk of the protein being retained on nontarget sequences while searching.

PRODORIC: state-of-the-art database of prokaryotic gene regulation

PRODORIC is worldwide one of the largest collections of prokaryotic transcription factor binding sites from multiple bacterial sources with corresponding interpretation and visualization tools. With the introduction of PRODORIC2 in 2017, the transition to a modern web interface and maintainable backend was started. With this latest PRODORIC release the database backend is now fully API-based and provides programmatical access to the complete PRODORIC data. The visualization tools Genome Browser and ProdoNet from the original PRODORIC have been reintroduced and were integrated into the PRODORIC website. Missing input and output options from the original Virtual Footprint were added again for position weight matrix pattern-based searches. The whole PRODORIC dataset was reannotated. Every transcription factor binding site was re-evaluated to increase the overall database quality. During this process, additional parameters, like bound effectors, regulation type and different types of experimental evidence have been added for every transcription factor. Additionally, 109 new transcription factors and 6 new organisms have been added. PRODORIC is publicly available at https://www.prodoric.de.

Designed architectural proteins that tune DNA looping in bacteria

Architectural proteins alter the shape of DNA. Some distort the double helix by introducing sharp kinks. This can serve to relieve strain in tightly-bent DNA structures. Here, we design and test artificial architectural proteins based on a sequence-specific Transcription Activator-like Effector (TALE) protein, either alone or fused to a eukaryotic high mobility group B (HMGB) DNA-bending domain. We hypothesized that TALE protein binding would stiffen DNA to bending and twisting, acting as an architectural protein that antagonizes the formation of small DNA loops. In contrast, fusion to an HMGB domain was hypothesized to generate a targeted DNA-bending architectural protein that facilitates DNA looping. We provide evidence from Escherichia coli Lac repressor gene regulatory loops supporting these hypotheses in living bacteria. Both data fitting to a thermodynamic DNA looping model and sophisticated molecular modeling support the interpretation of these results. We find that TALE protein binding inhibits looping by stiffening DNA to bending and twisting, while the Nhp6A domain enhances looping by bending DNA without introducing twisting flexibility. Our work illustrates artificial approaches to sculpt DNA geometry with functional consequences. Similar approaches may be applicable to tune the stability of small DNA loops in eukaryotes.

Sensory perception in bacterial cyclic diguanylate signal transduction

Cyclic diguanylate (c-di-GMP) signal transduction systems provide bacteria with the ability to sense changing cell status or environmental conditions and then execute suitable physiological and social behaviors in response. In this review, we provide a comprehensive census of the stimuli and receptors that are linked to the modulation of intracellular c-di-GMP. Emerging evidence indicates that c-di-GMP networks sense light, surfaces, energy, redox potential, respiratory electron acceptors, temperature, and structurally diverse biotic and abiotic chemicals. Bioinformatic analysis of sensory domains in diguanylate cyclases and c-di-GMP-specific phosphodiesterases as well as the receptor complexes associated with them reveals that these functions are linked to a diverse repertoire of protein domain families. We describe the principles of stimulus perception learned from studying these modular sensory devices, illustrate how they are assembled in varied combinations with output domains, and summarize a system for classifying these sensor proteins based on their complexity. Biological information processing via c-di-GMP signal transduction not only is fundamental to bacterial survival in dynamic environments but also is being used to engineer gene expression circuitry and synthetic proteins with à la carte biochemical functionalities.

Coevolutionary methods enable robust design of modular repressors by reestablishing intra-protein interactions

Genetic sensors with unique combinations of DNA recognition and allosteric response can be created by hybridizing DNA-binding modules (DBMs) and ligand-binding modules (LBMs) from distinct transcriptional repressors. This module swapping approach is limited by incompatibility between DBMs and LBMs from different proteins, due to the loss of critical module-module interactions after hybridization. We determine a design strategy for restoring key interactions between DBMs and LBMs by using a computational model informed by coevolutionary traits in the LacI family. This model predicts the influence of proposed mutations on protein structure and function, quantifying the feasibility of each mutation for rescuing hybrid repressors. We accurately predict which hybrid repressors can be rescued by mutating residues to reinstall relevant module-module interactions. Experimental results confirm that dynamic ranges of gene expression induction were improved significantly in these mutants. This approach enhances the molecular and mechanistic understanding of LacI family proteins, and advances the ability to design modular genetic parts.

An updated classification and mechanistic insights into ligand binding of the substrate-binding proteins

Substrate-binding proteins (SBPs) mediate ligand translocation and have been classified into seven clusters (A-G). Although the substrate specificities of these clusters are known to some extent, their ligand-binding mechanism(s) remain(s) incompletely understood. In this study, the list of SBPs belonging to different clusters was updated (764 SBPs) compared to the previously reported study (504 SBPs). Furthermore, a new cluster referred to as cluster H was identified. Results reveal that SBPs follow different ligand-binding mechanisms. Intriguingly, the majority of the SBPs follow the "one domain movement" rather than the well-known "Venus Fly-trap" mechanism. Moreover, SBPs of a few clusters display subdomain conformational movement rather than the complete movement of the N- and C-terminal domains.

Deep representation learning improves prediction of LacI-mediated transcriptional repression

Recent progress in DNA synthesis and sequencing technology has enabled systematic studies of protein function at a massive scale. We explore a deep mutational scanning study that measured the transcriptional repression function of 43,669 variants of the Escherichia coli LacI protein. We analyze structural and evolutionary aspects that relate to how the function of this protein is maintained, including an in-depth look at the C-terminal domain. We develop a deep neural network to predict transcriptional repression mediated by the lac repressor of Escherichia coli using experimental measurements of variant function. When measured across 10 separate training and validation splits using 5,009 single mutations of the lac repressor, our best-performing model achieved a median Pearson correlation of 0.79, exceeding any previous model. We demonstrate that deep representation learning approaches, first trained in an unsupervised manner across millions of diverse proteins, can be fine-tuned in a supervised fashion using lac repressor experimental datasets to more effectively predict a variant's effect on repression. These findings suggest a deep representation learning model may improve the prediction of other important properties of proteins.

Substitutions at Nonconserved Rheostat Positions Modulate Function by Rewiring Long-Range, Dynamic Interactions

Amino acid substitutions at nonconserved protein positions can have noncanonical and "long-distance" outcomes on protein function. Such outcomes might arise from changes in the internal protein communication network, which is often accompanied by changes in structural flexibility. To test this, we calculated flexibilities and dynamic coupling for positions in the linker region of the lactose repressor protein. This region contains nonconserved positions for which substitutions alter DNA-binding affinity. We first chose to study 11 substitutions at position 52. In computations, substitutions showed long-range effects on flexibilities of DNA-binding positions, and the degree of flexibility change correlated with experimentally measured changes in DNA binding. Substitutions also altered dynamic coupling to DNA-binding positions in a manner that captured other experimentally determined functional changes. Next, we broadened calculations to consider the dynamic coupling between 17 linker positions and the DNA-binding domain. Experimentally, these linker positions exhibited a wide range of substitution outcomes: Four conserved positions tolerated hardly any substitutions ("toggle"), ten nonconserved positions showed progressive changes from a range of substitutions ("rheostat"), and three nonconserved positions tolerated almost all substitutions ("neutral"). In computations with wild-type lactose repressor protein, the dynamic couplings between the DNA-binding domain and these linker positions showed varied degrees of asymmetry that correlated with the observed toggle/rheostat/neutral substitution outcomes. Thus, we propose that long-range and noncanonical substitutions outcomes at nonconserved positions arise from rewiring long-range communication among functionally important positions. Such calculations might enable predictions for substitution outcomes at a range of nonconserved positions.

A Primer on the oxDNA Model of DNA: When to Use it, How to Simulate it and How to Interpret the Results

The oxDNA model of Deoxyribonucleic acid has been applied widely to systems in biology, biophysics and nanotechnology. It is currently available via two independent open source packages. Here we present a set of clearly documented exemplar simulations that simultaneously provide both an introduction to simulating the model, and a review of the model's fundamental properties. We outline how simulation results can be interpreted in terms of-and feed into our understanding of-less detailed models that operate at larger length scales, and provide guidance on whether simulating a system with oxDNA is worthwhile.

Energetics of twisted DNA topologies

Our goal is to review the main theoretical models used to calculate free energy changes associated with common, torsion-induced conformational changes in DNA and provide the resulting equations hoping to facilitate quantitative analysis of both in vitro and in vivo studies. This review begins with a summary of work regarding the energy change of the negative supercoiling-induced B- to L-DNA transition, followed by a discussion of the energetics associated with the transition to Z-form DNA. Finally, it describes the energy changes associated with the formation of DNA curls and plectonemes, which can regulate DNA-protein interactions and promote cross talk between distant DNA elements, respectively. The salient formulas and parameters for each scenario are summarized in table format to facilitate comparison and provide a concise, user-friendly resource.

The genotype-phenotype landscape of an allosteric protein

Allostery is a fundamental biophysical mechanism that underlies cellular sensing, signaling, and metabolism. Yet a quantitative understanding of allosteric genotype-phenotype relationships remains elusive. Here, we report the large-scale measurement of the genotype-phenotype landscape for an allosteric protein: the lac repressor from Escherichia coli, LacI. Using a method that combines long-read and short-read DNA sequencing, we quantitatively measure the dose-response curves for nearly 105 variants of the LacI genetic sensor. The resulting data provide a quantitative map of the effect of amino acid substitutions on LacI allostery and reveal systematic sequence-structure-function relationships. We find that in many cases, allosteric phenotypes can be quantitatively predicted with additive or neural-network models, but unpredictable changes also occur. For example, we were surprised to discover a new band-stop phenotype that challenges conventional models of allostery and that emerges from combinations of nearly silent amino acid substitutions.

Biomolecular Systems Engineering: Unlocking the Potential of Engineered Allostery via the Lactose Repressor Topology

Allosteric function is a critical component of many of the parts used to construct gene networks throughout synthetic biology. In this review, we discuss an emerging field of research and education, biomolecular systems engineering, that expands on the synthetic biology edifice-integrating workflows and strategies from protein engineering, chemical engineering, electrical engineering, and computer science principles. We focus on the role of engineered allosteric communication as it relates to transcriptional gene regulators-i.e., transcription factors and corresponding unit operations. In this review, we (a) explore allosteric communication in the lactose repressor LacI topology, (b) demonstrate how to leverage this understanding of allostery in the LacI system to engineer non-natural BUFFER and NOT logical operations, (c) illustrate how engineering workflows can be used to confer alternate allosteric functions in disparate systems that share the LacI topology, and (d) demonstrate how fundamental unit operations can be directed to form combinational logical operations.

A Fifth of the Protein World: Rossmann-like Proteins as an Evolutionarily Successful Structural unit

The Rossmann-like fold is the most prevalent and diversified doubly-wound superfold of ancient evolutionary origin. Rossmann-like domains are present in a variety of metabolic enzymes and are capable of binding diverse ligands. Discerning evolutionary relationships among these domains is challenging because of their diverse functions and ancient origin. We defined a minimal Rossmann-like structural motif (RLM), identified RLM-containing domains among known 3D structures (20%) and classified them according to their homologous relationships. New classifications were incorporated into our Evolutionary Classification of protein Domains (ECOD) database. We defined 156 homology groups (H-groups), which were further clustered into 123 possible homology groups (X-groups). Our analysis revealed that RLM-containing proteins constitute approximately 15% of the human proteome. We found that disease-causing mutations are more frequent within RLM domains than within non-RLM domains of these proteins, highlighting the importance of RLM-containing proteins for human health.

Plant Glycan Metabolism by Bifidobacteria

Members of the genus Bifidobacterium, of which the majority have been isolated as gut commensals, are Gram-positive, non-motile, saccharolytic, non-sporulating, anaerobic bacteria. Many bifidobacterial strains are considered probiotic and therefore are thought to bestow health benefits upon their host. Bifidobacteria are highly abundant among the gut microbiota of healthy, full term, breast-fed infants, yet the relative average abundance of bifidobacteria tends to decrease as the human host ages. Because of the inverse correlation between bifidobacterial abundance/prevalence and health, there has been an increasing interest in maintaining, increasing or restoring bifidobacterial populations in the infant, adult and elderly gut. In order to colonize and persist in the gastrointestinal environment, bifidobacteria must be able to metabolise complex dietary and/or host-derived carbohydrates, and be resistant to various environmental challenges of the gut. This is not only important for the autochthonous bifidobacterial species colonising the gut, but also for allochthonous bifidobacteria provided as probiotic supplements in functional foods. For example, Bifidobacterium longum subsp. longum is a taxon associated with the metabolism of plant-derived poly/oligosaccharides in the adult diet, being capable of metabolising hemicellulose and various pectin-associated glycans. Many of these plant glycans are believed to stimulate the metabolism and growth of specific bifidobacterial species and are for this reason classified as prebiotics. In this review, bifidobacterial carbohydrate metabolism, with a focus on plant poly-/oligosaccharide degradation and uptake, as well as its associated regulation, will be discussed.

Dimerisation of the PICTS complex via LC8/Cut-up drives co-transcriptional transposon silencing in Drosophila

In animal gonads, the PIWI-interacting RNA (piRNA) pathway guards genome integrity in part through the co-transcriptional gene silencing of transposon insertions. In Drosophila ovaries, piRNA-loaded Piwi detects nascent transposon transcripts and instructs heterochromatin formation through the Panoramix-induced co-transcriptional silencing (PICTS) complex, containing Panoramix, Nxf2 and Nxt1. Here, we report that the highly conserved dynein light chain LC8/Cut-up (Ctp) is an essential component of the PICTS complex. Loss of Ctp results in transposon de-repression and a reduction in repressive chromatin marks specifically at transposon loci. In turn, Ctp can enforce transcriptional silencing when artificially recruited to RNA and DNA reporters. We show that Ctp drives dimerisation of the PICTS complex through its interaction with conserved motifs within Panoramix. Artificial dimerisation of Panoramix bypasses the necessity for its interaction with Ctp, demonstrating that conscription of a protein from a ubiquitous cellular machinery has fulfilled a fundamental requirement for a transposon silencing complex.

Characterization of the first tetrameric transcription factor of the GntR superfamily with allosteric regulation from the bacterial pathogen Agrobacterium fabrum

A species-specific region, denoted SpG8-1b allowing hydroxycinnamic acids (HCAs) degradation is important for the transition between the two lifestyles (rhizospheric versus pathogenic) of the plant pathogen Agrobacterium fabrum. Indeed, HCAs can be either used as trophic resources and/or as induced-virulence molecules. The SpG8-1b region is regulated by two transcriptional regulators, namely, HcaR (Atu1422) and Atu1419. In contrast to HcaR, Atu1419 remains so far uncharacterized. The high-resolution crystal structures of two fortuitous citrate complexes, two DNA complexes and the apoform revealed that the tetrameric Atu1419 transcriptional regulator belongs to the VanR group of Pfam PF07729 subfamily of the large GntR superfamily. Until now, GntR regulators were described as dimers. Here, we showed that Atu1419 represses three genes of the HCAs catabolic pathway. We characterized both the effector and DNA binding sites and identified key nucleotides in the target palindrome. From promoter activity measurement using defective gene mutants, structural analysis and gel-shift assays, we propose N5,N10-methylenetetrahydrofolate as the effector molecule, which is not a direct product/substrate of the HCA degradation pathway. The Zn2+ ion present in the effector domain has both a structural and regulatory role. Overall, our work shed light on the allosteric mechanism of transcription employed by this GntR repressor.

Structural Insight into the DNA Binding Function of Transcription Factor ERF

ETS family transcription factors control development of different cell types in humans, whereas deregulation of these proteins leads to severe developmental syndromes and cancers. One of a few members of the ETS family that are known to act solely as repressors, ERF, is required for normal osteogenesis and hematopoiesis. Another important function of ERF is acting as a tumor suppressor by antagonizing oncogenic fusions involving other ETS family factors. The structure of ERF and the DNA binding properties specific to this protein have not been elucidated. In this study, we determined two crystal structures of the complexes of the DNA binding domain of ERF with DNA. In one, ERF is in a distinct dimeric form, with Cys72 in a reduced state. In the other, two dimers of ERF are assembled into a tetramer that is additionally locked by two Cys72-Cys72 disulfide bonds across the dimers. In the tetramer, the ERF molecules are bound to a pseudocontinuous DNA on the same DNA face at two GGAA binding sites on opposite strands. Sedimentation velocity analysis showed that this tetrameric assembly forms on continuous DNA containing such tandem sites spaced by 7 bp. Our bioinformatic analysis of three previously reported sets of ERF binding loci across entire genomes showed that these loci were enriched in such 7 bp spaced tandem sites. Taken together, these results strongly suggest that the observed tetrameric assembly is a functional state of ERF in the human cell.

Synthetic gene-regulatory networks in the opportunistic human pathogen Streptococcus pneumoniae

Streptococcus pneumoniae is a major human pathogen responsible for enormous global morbidity and mortality. Despite this, the pneumococcus makes up part of the commensal nasopharyngeal flora. How the pneumococcus switches from this commensal to pathogenic state and causes disease is unclear and very likely involves variability in expression of its virulence factors. Here, we used synthetic biology approaches to generate complex gene-regulatory networks such as logic gates and toggle switches. We show that these networks are functional in vivo to control capsule production in an influenza-superinfection model. This opens the field of systematically testing the role of phenotypic variation in pneumococcal virulence. The approaches used here may serve as an example for synthetic biology projects in unrelated organisms.

Streptococcus pneumoniae can cause disease in various human tissues and organs, including the ear, the brain, the blood, and the lung, and thus in highly diverse and dynamic environments. It is challenging to study how pneumococci control virulence factor expression, because cues of natural environments and the presence of an immune system are difficult to simulate in vitro. Here, we apply synthetic biology methods to reverse-engineer gene expression control in S. pneumoniae. A selection platform is described that allows for straightforward identification of transcriptional regulatory elements out of combinatorial libraries. We present TetR- and LacI-regulated promoters that show expression ranges of four orders of magnitude. Based on these promoters, regulatory networks of higher complexity are assembled, such as logic AND gates and IMPLY gates. We demonstrate single-copy genome-integrated toggle switches that give rise to bimodal population distributions. The tools described here can be used to mimic complex expression patterns, such as the ones found for pneumococcal virulence factors. Indeed, we were able to rewire gene expression of the capsule operon, the main pneumococcal virulence factor, to be externally inducible (YES gate) or to act as an IMPLY gate (only expressed in absence of inducer). Importantly, we demonstrate that these synthetic gene-regulatory networks are functional in an influenza A virus superinfection murine model of pneumonia, paving the way for in vivo investigations of the importance of gene expression control on the pathogenicity of S. pneumoniae.

Characterization of Gene Repression by Designed Transcription Activator-like Effector Dimer Proteins

Gene regulation by control of transcription initiation is a fundamental property of living cells. Much of our understanding of gene repression originated from studies of the Escherichia coli lac operon switch, in which DNA looping plays an essential role. To validate and generalize principles from lac for practical applications, we previously described artificial DNA looping driven by designed transcription activator-like effector dimer (TALED) proteins. Because TALE monomers bind the idealized symmetrical lac operator sequence in two orientations, our prior studies detected repression due to multiple DNA loops. We now quantitatively characterize gene repression in living E. coli by a collection of individual TALED loops with systematic loop length variation. Fitting of a thermodynamic model allows unequivocal demonstration of looping and comparison of the engineered TALED repression system with the natural lac repressor system.

Structural basis of a novel repressor, SghR, controlling Agrobacterium infection by cross-talking to plants

Agrobacterium tumefaciens infects various plants and causes crown gall diseases involving temporal expression of virulence factors. SghA is a newly identified virulence factor enzymatically releasing salicylic acid from its glucoside conjugate and controlling plant tumor development. Here, we report the structural basis of SghR, a LacI-type transcription factor highly conserved in Rhizobiaceae family, regulating the expression of SghA and involved in tumorigenesis. We identified and characterized the binding site of SghR on the promoter region of sghA and then determined the crystal structures of apo-SghR, SghR complexed with its operator DNA, and ligand sucrose, respectively. These results provide detailed insights into how SghR recognizes its cognate DNA and shed a mechanistic light on how sucrose attenuates the affinity of SghR with DNA to modulate the expression of SghA. Given the important role of SghR in mediating the signaling cross-talk during Agrobacterium infection, our results pave the way for structure-based inducer analog design, which has potential applications for agricultural industry.

Mapping Protein-Protein Interaction Interface Peptides with Jun-Fos Assisted Phage Display and Deep Sequencing

Protein-protein interactions govern many cellular processes, and identifying binding interaction sites on proteins can facilitate the discovery of inhibitors to block such interactions. Here we identify peptides from a randomly fragmented plasmid encoding the β-lactamase inhibitory protein (BLIP) and the Lac repressor (LacI) that represent regions of protein-protein interactions. We utilized a Jun-Fos-assisted phage display system that has previously been used to screen cDNA and genomic libraries to identify antibody antigens. Affinity selection with polyclonal antibodies against LacI or BLIP resulted in the rapid enrichment of in-frame peptides from various regions of the proteins. Further, affinity selection with β-lactamase enriched peptides that encompass regions of BLIP previously shown to contribute strongly to the binding energy of the BLIP/β-lactamase interaction, i.e., hotspot residues. Further, one of the regions enriched by affinity selection encompassed a disulfide-constrained region of BLIP that forms part of the BLIP interaction surface in the native complex that we show also binds to β-lactamase as a disulfide-constrained macrocycle peptide with a K_D of ∼1 μM. Fragmented open reading frame (ORF) libraries may efficiently identify such naturally constrained peptides at protein-protein interaction interfaces. With sufficiently deep coverage of ORFs by peptide-coding inserts, phage display and deep sequencing can provide detailed information on the domains or peptides that contribute to an interaction. Such information should enable the design of potentially therapeutic macrocycles or peptidomimetics that block the interaction.

The strengths and limitations of using biolayer interferometry to monitor equilibrium titrations of biomolecules

Every method used to quantify biomolecular interactions has its own strengths and limitations. To quantify protein-DNA binding affinities, nitrocellulose filter binding assays with 32 P-labeled DNA quantify Kd values from 10-12 to 10-8 M but have several technical limitations. Here, we considered the suitability of biolayer interferometry (BLI), which monitors association and dissociation of a soluble macromolecule to an immobilized species; the ratio koff /kon determines Kd . However, for lactose repressor protein (LacI) and an engineered repressor protein ("LLhF") binding immobilized DNA, complicated kinetic curves precluded this analysis. Thus, we determined whether the amplitude of the BLI signal at equilibrium related linearly to the fraction of protein bound to DNA. A key question was the effective concentration of immobilized DNA. Equilibrium titration experiments with DNA concentrations below Kd (equilibrium binding regime) must be analyzed differently than those with DNA near or above Kd (stoichiometric binding regime). For ForteBio streptavidin tips, the most frequent effective DNA concentration was ~2 × 10-9 M. Although variation occurred among different lots of sensor tips, binding events with Kd ≥ 10-8 M should reliably be in the equilibrium binding regime. We also observed effects from multi-valent interactions: Tetrameric LacI bound two immobilized DNAs whereas dimeric LLhF did not. We next used BLI to quantify the amount of inducer sugars required to allosterically diminish protein-DNA binding and to assess the affinity of fructose-1-kinase for the DNA-LLhF complex. Overall, when experimental design corresponded with appropriate data interpretation, BLI was convenient and reliable for monitoring equilibrium titrations and thereby quantifying a variety of binding interactions.

The lac repressor hinge helix in context: The effect of the DNA binding domain and symmetry

The Lac system of genes has been an important model system in understanding gene regulation. When the dimer lac repressor protein binds to the correct DNA sequence, the hinge region of the protein goes through a disorder to order transition. The hinge region is disordered when binding to nonoperator sequences. This region of the protein must pay a conformational entropic penalty to order when it is bound to operator DNA. Structural studies show that this region is flexible. Previous simulations showed that this region is disordered when free in solution without the DNA binding domain present. Our simulations corroborate that this region is extremely flexible in solution, but we find that the presence of the DNA binding domain proximal to the hinge helix and salt make the ordered conformation more favorable even without DNA present.

Enhancement of LacI binding in vivo

Transcription factors (TFs) bind to specific sequences in DNA to regulate transcription. Despite extensive measurements of TFs’ dissociation constant (K_d) in vitro, their apparent K_din vivo are usually unknown. LacI, a bacterial TF, is often used to artificially recruit proteins onto eukaryotic genomes. As LacI binds tightly to its recognition site (LacO) in vitro with a K_d about 10 picomolar (pM), it is often assumed that LacI also has high affinity to LacO in vivo. In this work, we measured LacI binding in living yeast cells using a fluorescent repressor operator system and found an apparent K_d of ∼0.6 μM, four orders of magnitude higher than that in vitro. By genetically altering (i) GFP-LacI structure, (ii) GFP-LacI stability, (iii) chromosome accessibility and (iv) LacO sequence, we reduced the apparent K_d to <10 nM. It turns out that the GFP tagging location and the fusion protein stability have a large effect on LacI binding, but surprisingly, chromosome accessibility only plays a mild role. These findings contribute to our quantitative understanding of the features that affect the apparent K_d of TF in cells. They also provide guidance for future design of more specific chromosomal recruitment through high-affinity TFs.

Engineering repressors with coevolutionary cues facilitates toggle switches with a master reset

Engineering allosteric transcriptional repressors containing an environmental sensing module (ESM) and a DNA recognition module (DRM) has the potential to unlock a combinatorial set of rationally designed biological responses. We demonstrated that constructing hybrid repressors by fusing distinct ESMs and DRMs provides a means to flexibly rewire genetic networks for complex signal processing. We have used coevolutionary traits among LacI homologs to develop a model for predicting compatibility between ESMs and DRMs. Our predictions accurately agree with the performance of 40 engineered repressors. We have harnessed this framework to develop a system of multiple toggle switches with a master OFF signal that produces a unique behavior: each engineered biological activity is switched to a stable ON state by different chemicals and returned to OFF in response to a common signal. One promising application of this design is to develop living diagnostics for monitoring multiple parameters in complex physiological environments and it represents one of many circuit topologies that can be explored with modular repressors designed with coevolutionary information.

Predictive shifts in free energy couple mutations to their phenotypic consequences

Mutation is a critical mechanism by which evolution explores the functional landscape of proteins. Despite our ability to experimentally inflict mutations at will, it remains difficult to link sequence-level perturbations to systems-level responses. Here, we present a framework centered on measuring changes in the free energy of the system to link individual mutations in an allosteric transcriptional repressor to the parameters which govern its response. We find that the energetic effects of the mutations can be categorized into several classes which have characteristic curves as a function of the inducer concentration. We experimentally test these diagnostic predictions using the well-characterized LacI repressor of Escherichia coli, probing several mutations in the DNA binding and inducer binding domains. We find that the change in gene expression due to a point mutation can be captured by modifying only the model parameters that describe the respective domain of the wild-type protein. These parameters appear to be insulated, with mutations in the DNA binding domain altering only the DNA affinity and those in the inducer binding domain altering only the allosteric parameters. Changing these subsets of parameters tunes the free energy of the system in a way that is concordant with theoretical expectations. Finally, we show that the induction profiles and resulting free energies associated with pairwise double mutants can be predicted with quantitative accuracy given knowledge of the single mutants, providing an avenue for identifying and quantifying epistatic interactions.